Your genes code for what diseases you might get, whether you are good at math or music, how good your memory is, what you look like, what you sound like, how you feel, how long you’ll likely live, and more.

This means that if we can decipher this genomic “code,” we can predict your biological future and proactively work to anticipate and improve your health.

It’s a data problem — and if you are a data scientist or machine-learning expert, it is the most challenging, interesting and important problem you could ever try to tackle.

In the simplest terms, sequencing a genome means turning DNA into a series of four letters that looks like this:

ACAAGATGCCATTGTCCCCCGGCCTCCTGCTG

Each person’s genome produces a text file that is about 300 gigabytes.

“The big thing is the mission — the ability to affect humanity in a positive way. If you are a data scientist, why focus on making a better messaging app or better Internet advertising, when you could be advancing the understanding of disease to make sick people better and of aging to make people live longer, healthier lives?”

“The big mission is to learn how to interpret the human genome — to be able to predict anything that can be predicted from the source code that runs us.”

Here is Peter Diamandis explaining —

It’s a Translation Problem, “Like Google Translate”

HLI is creating an “integrated health record” for everyone entering its database. The data sets created will include the following:

Genomic: The 3.2 billion nucleotides from your mother, and the 3.2 billion nucleotides from your father.

Microbiome: The genome of the 100 trillion + microorganisms living in our bodies. There are 10 times as many microbial cells than human cells, and their effects on our bodies are enormous and massively understudied.

Physiological Health Data: All of the data we can collect on ourselves. Our vital signs, blood glucose levels, micro RNAs in the bloodstream, heart rate, VO2…

Translating between all of this data and your health outcome is, metaphorically, similar to how Google Translate works.

Google Translate (GT) uses a process called statistical machine translation, which means that GT generates translations based on patterns found in large amounts of written text.

Rather than attempt to teach the computer every rule of every language, this approach lets the computer discover the rules for themselves based on statistically significant patterns in the data.

Once it finds these patterns (patterns that are unlikely to occur by chance), it can use this “model” to translate similar text in the future.

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Now, in the moment of history of science that we witness technology’s momentum pushing forward, venture capital following, and the genetic sciences take digital leaps forward, it’s time to pause….

Point – Counterpoint

As the aspirational goals of DNA science advances let us pause to consider a perspective being articulated by scientists, another point of view less optimistic.

What are the potential adverse consequences of ‘Code of Life’ research and intervention?

As the digital-biological nexus is established and the funding proceeds, there are those who feel a moratorium is called for now, and a larger debate has become ripe, in legal terms, for larger ethical, societal and consequential decisions…